What is data aggregation?  (Types, use cases, and tools)

Carly Fiorina once said, “The goal is to transform data into information, and information into insight.”

Explanation: the real power of data is how it’s used to create meaningful information that leads to practical actions and decisions. And one of the best ways to achieve this is to use data aggregation.

What is data aggregation, and what tools should you use to aggregate data?

Key takeaways:

• Data aggregation is the process of collecting and combining data from multiple sources to create a summary or a more comprehensive dataset.
• Data aggregation is used in business analytics, market research, healthcare, financial reporting, and more.
• There are mainly two types of data aggregation: time and spatial aggregation and manual and automated aggregation.
• Sheetgo is a tool that automates data aggregation.

What is data aggregation?

Data aggregation is the process of collecting and combining data from multiple sources to create a summary or a more comprehensive dataset.

How does data aggregation work?

Let’s use a simple example to understand how data aggregation works.

Imagine you want to know the number of apples 100 people in your neighborhood have. You can go to each person’s house and count all the apples one by one. But this is not productive; you still have 99 people to visit.

What’s the best solution?

You ask each person to count their apples alone (before you visit them) and give you the total number. Then, you add up all those totals to get one big number that represents all the apples in the entire neighborhood.

Data aggregation works the same way. It gathers information from many websites, databases, or other data sources and then combines it into a single report or dataset. Businesses, researchers, or anyone else can analyze this report and make important decisions.

4 Use cases of data aggregation

1. Business analytics

In a company, different departments like sales, marketing, and customer service often work in their own silos. Each of them collects data relevant to their specific operations.

• Sales might track the number of products sold,
• Marketing might monitor the performance of advertising campaigns, and
• Customer service might log customer complaints and feedback.

While each department generates important data, analyzing these data sets separately can be difficult. It’s also difficult to get a complete picture of the business’s overall health.

This is where data aggregation comes in. When the company combines this data, they can see the number of products sold, how marketing helped them sell these products, and what customers think about the products.

2. Market research

Companies do market research to understand what customers want and how they behave and find new trends. To do this, they gather information from many places. This information can include

• Customer surveys,
• Social media activity,
• Competitor analysis,
• Sales data,
• and more.

However, chances are the company will have one customer survey report, competitor report, sales report, and so on. Just imagine the nightmare trying to analyze each of them. If you aggregate the data, you’ll create one single report that combines this information.

3. Healthcare

Hospitals and clinics collect patient data from electronic health records, lab tests, and imaging reports. With data aggregation, they can get a view of a patient’s health and better diagnose and treat patients.

It also helps in research, like tracking the spread of diseases or the effectiveness of treatments.

4. Financial Reporting

Companies often collect data from many departments, such as sales, marketing, and customer service. When they aggregate this data, they can know the overall business performance.

For example, combining sales data from different regions helps a company understand which areas are performing best and where improvements are needed.

Types of data aggregation

1. Time and spatial aggregation

Time aggregation is about collecting data points for a single source over a defined time period. So, if you wanted to track how much your favorite store sold each day for the past month, that would be time aggregation.

On the other hand, spatial aggregation is a method used to collect data points for a group of resources over a given time period. For example, you use it to know how much all the stores in your neighborhood sold last month.

2. Manual and automated aggregation

In manual data aggregation, individuals collect, organize, and analyze data manually. They often use tools like spreadsheets or databases. While this approach is flexible and gives more control, it’s time-consuming and prone to errors. The larger the datasets, the more challenging the task is.

With automated data aggregation, you use software tools (like Sheetgo) to collect, process, and analyze data automatically. This approach is more efficient, accurate, and scalable. It’s the best for handling large and complex datasets.

Now that you understand data aggregation and its various types, you might want to know how to aggregate data. So, how about we see a more practical example? We will focus on automated data aggregation and use Sheetgo, a tool that can save time and money.

How can Sheetgo help with data aggregation?

Sheetgo can help with data aggregation by collecting data from various spreadsheets (Google Sheets and Excel) and combining it into one or multiple spreadsheets.

Let’s say an HR department needs to monitor 37 employee attendance status for one day. They want to know which employee clocked in today.

When clocking in and out, employees press a button in an online tool, which adds the information to a Google Sheet. And if, for some reason, they cannot work, they need to use the “Absent” status.

In total, we have 4 Google Sheets (IT, Sales, Marketing, and Customer Support), and each sheet has the following columns: ID, name, department, check-in, check-out, leave, and attendance status.

The HR department wants to collect each document’s information into one master sheet. If an HR member has to manually scan each data point, it will take hours. However, using an automated data aggregation tool like Sheetgo will dramatically improve productivity.

Here is how:

1. Log into your Sheetgo account, click “New” then “Blank Workflow”. You can create a free account here.

2. Choose “Create an automation.”

3. Select “Multiple files.”

4. Click “Select File.”

5. Choose the spreadsheets you want to gather data from and click “Done.”

6.  Click the “Next step” button.

7. Now, choose “Condition” to filter data from the four data sources.

8. In the next tab, select the column you want to get the information from. Choose “Text is exactly,” and enter the name of the text Sheetgo needs to filter. In my case, I set “Column G: Attendance Status,” and the text is “Absent.”

Click “Confirm” and “Next step.”

9. Click “Google Sheets.”

10. Next, select or create the destination file. Sheetgo will use this file or spreadsheet to report all “Absent” attendance statuses. Click “Finish and save.”

11. Sheetgo will now automatically scan your departments to track attendance, as you can see in the image below.

12. Finally, Sheetgo will create a report displaying the attendance from each department.

Did you see how automated data aggregation works? Thanks to this Google Sheet automation, you can focus on more important tasks while tracking attendance status in your company.

You can use Sheetgo with Google Sheets and Excel to automate your finance, HR, CRM, supply chain, and more.

FAQ

Why should data be aggregated?

Data should be aggregated to simplify large datasets, uncover patterns, and support decision-making. It transforms scattered information into meaningful insights.

Why is data aggregation important?

Data aggregation is important because it helps businesses understand trends, make informed decisions, and improve overall performance.

How can you aggregate data?

You can aggregate data through methods like summing, averaging, counting, and grouping, and using tools like spreadsheets, databases, and specialized software.

What are the best data aggregation tools?

The best data aggregation tools are 1. Sheetgo, 2. Looker Studio, 3. Stata, 4. Google Analytics, and 5. Alteryx.